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99 lines
4.0 KiB
99 lines
4.0 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/gather.cu.h"
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#include "paddle/fluid/operators/gather_op.h"
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#include "paddle/fluid/operators/scatter.cu.h"
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#include "paddle/fluid/operators/scatter_op.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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class ScatterOpCUDAKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext &ctx) const override {
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PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
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"This kernel only runs on GPU device.");
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auto *X = ctx.Input<Tensor>("X");
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auto *Ids = ctx.Input<Tensor>("Ids");
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auto *Updates = ctx.Input<Tensor>("Updates");
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auto *Out = ctx.Output<Tensor>("Out");
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bool overwrite = ctx.Attr<bool>("overwrite");
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Out->ShareDataWith(*X);
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// use template class to support int32_t and int64_t
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const auto &index_type = Ids->type();
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bool index_type_match = index_type == framework::proto::VarType::INT32 ||
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index_type == framework::proto::VarType::INT64;
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PADDLE_ENFORCE_EQ(
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index_type_match, true,
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"scatter_op Index holds the wrong type, it holds %s, but desires to be "
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"%s or %s",
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paddle::framework::DataTypeToString(index_type),
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paddle::framework::DataTypeToString(framework::proto::VarType::INT32),
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paddle::framework::DataTypeToString(framework::proto::VarType::INT64));
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if (index_type == framework::proto::VarType::INT32) {
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GPUScatterAssign<T, int32_t>(ctx, *Updates, *Ids, Out, overwrite);
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} else {
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GPUScatterAssign<T, int64_t>(ctx, *Updates, *Ids, Out, overwrite);
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}
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}
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};
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template <typename T>
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class ScatterGradOpCUDAKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext &ctx) const override {
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PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
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"This kernel only runs on GPU device.");
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auto *dX = ctx.Output<Tensor>(framework::GradVarName("X"));
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auto *dUpdates = ctx.Output<Tensor>(framework::GradVarName("Updates"));
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auto *Ids = ctx.Input<Tensor>("Ids");
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auto *dOut = ctx.Input<Tensor>(framework::GradVarName("Out"));
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if (dX) {
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// In place gradient: dX = dO
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framework::TensorCopy(*dOut, ctx.GetPlace(), dX);
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}
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if (dUpdates) {
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dUpdates->mutable_data<T>(ctx.GetPlace());
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// Gradient by Gather: dUpdates = dO[Ids]
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const auto &index_type = Ids->type();
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bool index_type_match = index_type == framework::proto::VarType::INT32 ||
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index_type == framework::proto::VarType::INT64;
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PADDLE_ENFORCE_EQ(
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index_type_match, true,
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"scatter_op Index holds the wrong type, it holds %s, but desires to "
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"be %s or %s",
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paddle::framework::DataTypeToString(index_type),
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paddle::framework::DataTypeToString(framework::proto::VarType::INT32),
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paddle::framework::DataTypeToString(
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framework::proto::VarType::INT64));
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// Gradient by Gather: dUpdates = dO[Ids]
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if (index_type == framework::proto::VarType::INT32) {
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GPUGather<T, int32_t>(ctx.device_context(), *dOut, *Ids, dUpdates);
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} else {
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GPUGather<T, int64_t>(ctx.device_context(), *dOut, *Ids, dUpdates);
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}
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_CUDA_KERNEL(scatter, ops::ScatterOpCUDAKernel<float>);
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REGISTER_OP_CUDA_KERNEL(scatter_grad, ops::ScatterGradOpCUDAKernel<float>);
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